{"id":"W2994881336","doi":"10.1109/iemcon.2019.8936303","title":"Stopping Criterion for Belief Propagation Polar Code Decoders based on Bits Difference Ratio","year":2019,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Decoding methods; Belief propagation; Computer science; Early stopping; Algorithm; Reduction (mathematics); Constraint (computer-aided design); Polar; Polar code; Bit error rate; Code (set theory); Latency (audio); Optimal stopping; Propagation of uncertainty; Mathematics; Mathematical optimization; Telecommunications; Artificial intelligence; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003904917,0.0001564386,0.0001494575,0.0001798123,0.0001266576,0.0001735823,0.0005594884,0.00007320131,0.00001357367],"category_scores_gemma":[0.0001460245,0.0001397794,0.00006036975,0.0002298067,0.00001420346,0.0003592946,0.0000772488,0.0001156395,0.00003375315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009727361,"about_ca_system_score_gemma":0.00008904253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003854829,"about_ca_topic_score_gemma":0.0000517737,"domain_scores_codex":[0.9987161,0.00006803723,0.000214739,0.0004796132,0.0002641937,0.0002572913],"domain_scores_gemma":[0.9988433,0.0002542066,0.0001079451,0.0005873632,0.0001535567,0.00005365681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001840626,0.0006312918,0.02674163,0.0005022248,0.00003239891,0.000006247497,0.00283718,0.003781541,0.5970268,0.1509906,0.004540454,0.2127257],"study_design_scores_gemma":[0.0002970467,0.0004489542,0.002829775,0.0001042774,0.000002700326,0.000001544518,0.00001275834,0.9089399,0.08580048,0.0009415736,0.0004062043,0.0002147655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.056642,0.000007467961,0.9387739,0.001199287,0.000394424,0.0008177007,0.000002684437,0.0008651105,0.001297408],"genre_scores_gemma":[0.8337739,8.937593e-7,0.1642234,0.001282608,0.00002379607,0.00006691502,0.000007312186,0.00001406525,0.0006071065],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9051584,"threshold_uncertainty_score":0.5700037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02174396247809076,"score_gpt":0.2751785140212802,"score_spread":0.2534345515431894,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}